Overview

Dataset statistics

Number of variables44
Number of observations4645
Missing cells41921
Missing cells (%)20.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 MiB
Average record size in memory375.0 B

Variable types

Categorical21
Text7
DateTime4
Unsupported7
Numeric4
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-18432/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (69.3%)Imbalance
여성종사자수 is highly imbalanced (63.4%)Imbalance
영업장주변구분명 is highly imbalanced (75.5%)Imbalance
등급구분명 is highly imbalanced (74.0%)Imbalance
총인원 is highly imbalanced (73.9%)Imbalance
공장판매직종업원수 is highly imbalanced (53.1%)Imbalance
보증액 is highly imbalanced (69.6%)Imbalance
월세액 is highly imbalanced (69.7%)Imbalance
인허가취소일자 has 4645 (100.0%) missing valuesMissing
폐업일자 has 828 (17.8%) missing valuesMissing
휴업시작일자 has 4645 (100.0%) missing valuesMissing
휴업종료일자 has 4645 (100.0%) missing valuesMissing
재개업일자 has 4645 (100.0%) missing valuesMissing
전화번호 has 2695 (58.0%) missing valuesMissing
소재지면적 has 882 (19.0%) missing valuesMissing
도로명주소 has 1659 (35.7%) missing valuesMissing
도로명우편번호 has 1674 (36.0%) missing valuesMissing
좌표정보(X) has 109 (2.3%) missing valuesMissing
좌표정보(Y) has 109 (2.3%) missing valuesMissing
다중이용업소여부 has 725 (15.6%) missing valuesMissing
시설총규모 has 725 (15.6%) missing valuesMissing
전통업소지정번호 has 4645 (100.0%) missing valuesMissing
전통업소주된음식 has 4645 (100.0%) missing valuesMissing
홈페이지 has 4645 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 36.34181329)Skewed
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 has 3042 (65.5%) zerosZeros

Reproduction

Analysis started2024-05-11 06:21:35.677205
Analysis finished2024-05-11 06:21:37.889975
Duration2.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
3050000
4645 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 4645
100.0%

Length

2024-05-11T15:21:37.983639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:38.132478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 4645
100.0%

관리번호
Text

UNIQUE 

Distinct4645
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
2024-05-11T15:21:38.386899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters102190
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4645 ?
Unique (%)100.0%

Sample

1st row3050000-107-1972-00080
2nd row3050000-107-1972-00081
3rd row3050000-107-1972-00698
4th row3050000-107-1972-00710
5th row3050000-107-1972-00711
ValueCountFrequency (%)
3050000-107-1972-00080 1
 
< 0.1%
3050000-107-2018-00059 1
 
< 0.1%
3050000-107-2018-00039 1
 
< 0.1%
3050000-107-2018-00038 1
 
< 0.1%
3050000-107-2018-00037 1
 
< 0.1%
3050000-107-2018-00036 1
 
< 0.1%
3050000-107-2018-00035 1
 
< 0.1%
3050000-107-2018-00041 1
 
< 0.1%
3050000-107-2018-00034 1
 
< 0.1%
3050000-107-2018-00032 1
 
< 0.1%
Other values (4635) 4635
99.8%
2024-05-11T15:21:38.933781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 46266
45.3%
- 13935
 
13.6%
1 10117
 
9.9%
2 7160
 
7.0%
7 6195
 
6.1%
3 6140
 
6.0%
5 6018
 
5.9%
9 2182
 
2.1%
8 1459
 
1.4%
4 1370
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88255
86.4%
Dash Punctuation 13935
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46266
52.4%
1 10117
 
11.5%
2 7160
 
8.1%
7 6195
 
7.0%
3 6140
 
7.0%
5 6018
 
6.8%
9 2182
 
2.5%
8 1459
 
1.7%
4 1370
 
1.6%
6 1348
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 13935
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 102190
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46266
45.3%
- 13935
 
13.6%
1 10117
 
9.9%
2 7160
 
7.0%
7 6195
 
6.1%
3 6140
 
6.0%
5 6018
 
5.9%
9 2182
 
2.1%
8 1459
 
1.4%
4 1370
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 102190
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46266
45.3%
- 13935
 
13.6%
1 10117
 
9.9%
2 7160
 
7.0%
7 6195
 
6.1%
3 6140
 
6.0%
5 6018
 
5.9%
9 2182
 
2.1%
8 1459
 
1.4%
4 1370
 
1.3%
Distinct3137
Distinct (%)67.5%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
Minimum1972-03-30 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T15:21:39.171344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:21:39.415617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4645
Missing (%)100.0%
Memory size41.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
3
3817 
1
828 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
3 3817
82.2%
1 828
 
17.8%

Length

2024-05-11T15:21:39.674274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:39.818598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3817
82.2%
1 828
 
17.8%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
폐업
3817 
영업/정상
828 

Length

Max length5
Median length2
Mean length2.5347686
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
폐업 3817
82.2%
영업/정상 828
 
17.8%

Length

2024-05-11T15:21:39.953977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:40.074676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3817
82.2%
영업/정상 828
 
17.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
2
3817 
1
828 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 3817
82.2%
1 828
 
17.8%

Length

2024-05-11T15:21:40.194963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:40.307428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3817
82.2%
1 828
 
17.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
폐업
3817 
영업
828 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업
2nd row영업
3rd row영업
4th row영업
5th row영업

Common Values

ValueCountFrequency (%)
폐업 3817
82.2%
영업 828
 
17.8%

Length

2024-05-11T15:21:40.423507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:40.523844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3817
82.2%
영업 828
 
17.8%

폐업일자
Date

MISSING 

Distinct2558
Distinct (%)67.0%
Missing828
Missing (%)17.8%
Memory size36.4 KiB
Minimum1996-02-24 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T15:21:40.641471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:21:40.817808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4645
Missing (%)100.0%
Memory size41.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4645
Missing (%)100.0%
Memory size41.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4645
Missing (%)100.0%
Memory size41.0 KiB

전화번호
Text

MISSING 

Distinct1571
Distinct (%)80.6%
Missing2695
Missing (%)58.0%
Memory size36.4 KiB
2024-05-11T15:21:41.293585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.227692
Min length2

Characters and Unicode

Total characters19944
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1438 ?
Unique (%)73.7%

Sample

1st row0222135007
2nd row02 9624830
3rd row02 9620872
4th row0222491205
5th row0222124021
ValueCountFrequency (%)
02 1043
31.4%
031 75
 
2.3%
0222425611 28
 
0.8%
0222487800 27
 
0.8%
070 25
 
0.8%
9581002 24
 
0.7%
0221738000 24
 
0.7%
07043009589 23
 
0.7%
9662500 16
 
0.5%
032 15
 
0.5%
Other values (1641) 2020
60.8%
2024-05-11T15:21:41.932654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3945
19.8%
0 3476
17.4%
9 1902
9.5%
6 1580
7.9%
1578
 
7.9%
5 1330
 
6.7%
4 1326
 
6.6%
3 1300
 
6.5%
1 1206
 
6.0%
7 1163
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18366
92.1%
Space Separator 1578
 
7.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3945
21.5%
0 3476
18.9%
9 1902
10.4%
6 1580
8.6%
5 1330
 
7.2%
4 1326
 
7.2%
3 1300
 
7.1%
1 1206
 
6.6%
7 1163
 
6.3%
8 1138
 
6.2%
Space Separator
ValueCountFrequency (%)
1578
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19944
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3945
19.8%
0 3476
17.4%
9 1902
9.5%
6 1580
7.9%
1578
 
7.9%
5 1330
 
6.7%
4 1326
 
6.6%
3 1300
 
6.5%
1 1206
 
6.0%
7 1163
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19944
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3945
19.8%
0 3476
17.4%
9 1902
9.5%
6 1580
7.9%
1578
 
7.9%
5 1330
 
6.7%
4 1326
 
6.6%
3 1300
 
6.5%
1 1206
 
6.0%
7 1163
 
5.8%

소재지면적
Text

MISSING 

Distinct1017
Distinct (%)27.0%
Missing882
Missing (%)19.0%
Memory size36.4 KiB
2024-05-11T15:21:42.395148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.562583
Min length3

Characters and Unicode

Total characters17169
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique699 ?
Unique (%)18.6%

Sample

1st row12.40
2nd row21.94
3rd row25.50
4th row12.00
5th row13.50
ValueCountFrequency (%)
3.30 479
 
12.7%
00 171
 
4.5%
6.60 140
 
3.7%
33.00 116
 
3.1%
10.00 110
 
2.9%
3.00 98
 
2.6%
9.90 78
 
2.1%
16.50 76
 
2.0%
6.00 76
 
2.0%
13.20 64
 
1.7%
Other values (1007) 2355
62.6%
2024-05-11T15:21:43.080812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4623
26.9%
. 3763
21.9%
3 2055
12.0%
1 1311
 
7.6%
2 1194
 
7.0%
6 1055
 
6.1%
5 835
 
4.9%
4 709
 
4.1%
9 692
 
4.0%
8 513
 
3.0%
Other values (2) 419
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13405
78.1%
Other Punctuation 3764
 
21.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4623
34.5%
3 2055
15.3%
1 1311
 
9.8%
2 1194
 
8.9%
6 1055
 
7.9%
5 835
 
6.2%
4 709
 
5.3%
9 692
 
5.2%
8 513
 
3.8%
7 418
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 3763
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 17169
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4623
26.9%
. 3763
21.9%
3 2055
12.0%
1 1311
 
7.6%
2 1194
 
7.0%
6 1055
 
6.1%
5 835
 
4.9%
4 709
 
4.1%
9 692
 
4.0%
8 513
 
3.0%
Other values (2) 419
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17169
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4623
26.9%
. 3763
21.9%
3 2055
12.0%
1 1311
 
7.6%
2 1194
 
7.0%
6 1055
 
6.1%
5 835
 
4.9%
4 709
 
4.1%
9 692
 
4.0%
8 513
 
3.0%
Other values (2) 419
 
2.4%
Distinct162
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
2024-05-11T15:21:43.585361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1067815
Min length6

Characters and Unicode

Total characters28366
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)0.7%

Sample

1st row130854
2nd row130862
3rd row130867
4th row130854
5th row130854
ValueCountFrequency (%)
130851 869
18.7%
130817 424
 
9.1%
130864 414
 
8.9%
130865 222
 
4.8%
130848 188
 
4.0%
130835 160
 
3.4%
130840 110
 
2.4%
130836 103
 
2.2%
130805 98
 
2.1%
130826 97
 
2.1%
Other values (152) 1960
42.2%
2024-05-11T15:21:44.196383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6246
22.0%
0 5399
19.0%
3 5379
19.0%
8 4864
17.1%
5 1845
 
6.5%
6 1350
 
4.8%
4 1053
 
3.7%
7 1014
 
3.6%
2 547
 
1.9%
- 496
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27870
98.3%
Dash Punctuation 496
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6246
22.4%
0 5399
19.4%
3 5379
19.3%
8 4864
17.5%
5 1845
 
6.6%
6 1350
 
4.8%
4 1053
 
3.8%
7 1014
 
3.6%
2 547
 
2.0%
9 173
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 496
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28366
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6246
22.0%
0 5399
19.0%
3 5379
19.0%
8 4864
17.1%
5 1845
 
6.5%
6 1350
 
4.8%
4 1053
 
3.7%
7 1014
 
3.6%
2 547
 
1.9%
- 496
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28366
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6246
22.0%
0 5399
19.0%
3 5379
19.0%
8 4864
17.1%
5 1845
 
6.5%
6 1350
 
4.8%
4 1053
 
3.7%
7 1014
 
3.6%
2 547
 
1.9%
- 496
 
1.7%
Distinct2721
Distinct (%)58.6%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
2024-05-11T15:21:44.686402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length58
Mean length28.776103
Min length17

Characters and Unicode

Total characters133665
Distinct characters323
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2406 ?
Unique (%)51.8%

Sample

1st row서울특별시 동대문구 전농동 295-52 북동16호,남동특1호 (전농로147)
2nd row서울특별시 동대문구 제기동 630 [왕산로35길27]
3rd row서울특별시 동대문구 청량리동 61-320 (청소년3길14)
4th row서울특별시 동대문구 전농동 295-52 시장북동34호 (전농로147)
5th row서울특별시 동대문구 전농동 295-431 1층
ValueCountFrequency (%)
서울특별시 4642
19.4%
동대문구 4642
19.4%
전농동 1446
 
6.1%
제기동 966
 
4.0%
장안동 702
 
2.9%
591-53 692
 
2.9%
용두동 572
 
2.4%
청량리역,롯데백화점 525
 
2.2%
33-1 427
 
1.8%
1층 395
 
1.7%
Other values (2956) 8864
37.1%
2024-05-11T15:21:45.723428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23280
 
17.4%
10011
 
7.5%
1 6100
 
4.6%
5221
 
3.9%
4908
 
3.7%
4850
 
3.6%
4733
 
3.5%
4710
 
3.5%
4692
 
3.5%
4643
 
3.5%
Other values (313) 60517
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 77963
58.3%
Decimal Number 24754
 
18.5%
Space Separator 23280
 
17.4%
Dash Punctuation 4131
 
3.1%
Open Punctuation 1179
 
0.9%
Close Punctuation 1179
 
0.9%
Other Punctuation 643
 
0.5%
Uppercase Letter 508
 
0.4%
Lowercase Letter 26
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10011
 
12.8%
5221
 
6.7%
4908
 
6.3%
4850
 
6.2%
4733
 
6.1%
4710
 
6.0%
4692
 
6.0%
4643
 
6.0%
4643
 
6.0%
1639
 
2.1%
Other values (269) 27913
35.8%
Uppercase Letter
ValueCountFrequency (%)
B 163
32.1%
K 150
29.5%
S 147
28.9%
A 16
 
3.1%
C 12
 
2.4%
M 4
 
0.8%
U 2
 
0.4%
O 2
 
0.4%
D 2
 
0.4%
G 2
 
0.4%
Other values (8) 8
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 6100
24.6%
3 3613
14.6%
2 2699
10.9%
5 2613
10.6%
9 2322
 
9.4%
0 2004
 
8.1%
6 1707
 
6.9%
4 1464
 
5.9%
7 1153
 
4.7%
8 1079
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 628
97.7%
@ 6
 
0.9%
: 5
 
0.8%
? 3
 
0.5%
/ 1
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
k 13
50.0%
s 12
46.2%
e 1
 
3.8%
Open Punctuation
ValueCountFrequency (%)
( 907
76.9%
[ 272
 
23.1%
Close Punctuation
ValueCountFrequency (%)
) 907
76.9%
] 272
 
23.1%
Space Separator
ValueCountFrequency (%)
23280
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4131
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 77963
58.3%
Common 55168
41.3%
Latin 534
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10011
 
12.8%
5221
 
6.7%
4908
 
6.3%
4850
 
6.2%
4733
 
6.1%
4710
 
6.0%
4692
 
6.0%
4643
 
6.0%
4643
 
6.0%
1639
 
2.1%
Other values (269) 27913
35.8%
Common
ValueCountFrequency (%)
23280
42.2%
1 6100
 
11.1%
- 4131
 
7.5%
3 3613
 
6.5%
2 2699
 
4.9%
5 2613
 
4.7%
9 2322
 
4.2%
0 2004
 
3.6%
6 1707
 
3.1%
4 1464
 
2.7%
Other values (13) 5235
 
9.5%
Latin
ValueCountFrequency (%)
B 163
30.5%
K 150
28.1%
S 147
27.5%
A 16
 
3.0%
k 13
 
2.4%
s 12
 
2.2%
C 12
 
2.2%
M 4
 
0.7%
U 2
 
0.4%
O 2
 
0.4%
Other values (11) 13
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 77963
58.3%
ASCII 55702
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23280
41.8%
1 6100
 
11.0%
- 4131
 
7.4%
3 3613
 
6.5%
2 2699
 
4.8%
5 2613
 
4.7%
9 2322
 
4.2%
0 2004
 
3.6%
6 1707
 
3.1%
4 1464
 
2.6%
Other values (34) 5769
 
10.4%
Hangul
ValueCountFrequency (%)
10011
 
12.8%
5221
 
6.7%
4908
 
6.3%
4850
 
6.2%
4733
 
6.1%
4710
 
6.0%
4692
 
6.0%
4643
 
6.0%
4643
 
6.0%
1639
 
2.1%
Other values (269) 27913
35.8%

도로명주소
Text

MISSING 

Distinct1730
Distinct (%)57.9%
Missing1659
Missing (%)35.7%
Memory size36.4 KiB
2024-05-11T15:21:46.203044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length56
Mean length35.944742
Min length23

Characters and Unicode

Total characters107331
Distinct characters302
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1524 ?
Unique (%)51.0%

Sample

1st row서울특별시 동대문구 왕산로35길 27 (제기동,[왕산로35길27])
2nd row서울특별시 동대문구 제기로33길 5 (청량리동,(청소년3길14))
3rd row서울특별시 동대문구 전농로15길 21, 1층 (전농동, 제2서-2)
4th row서울특별시 동대문구 한빛로 58-2 (용두동,(2호) [한빛로58-2])
5th row서울특별시 동대문구 제기로6길 18 (제기동,지상1층)
ValueCountFrequency (%)
서울특별시 2984
 
15.0%
동대문구 2984
 
15.0%
전농동 934
 
4.7%
1층 912
 
4.6%
왕산로 818
 
4.1%
214 738
 
3.7%
제기동 461
 
2.3%
지하2층 433
 
2.2%
장안동 389
 
2.0%
청량리역,롯데백화점 375
 
1.9%
Other values (1576) 8900
44.7%
2024-05-11T15:21:46.983795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16997
 
15.8%
6789
 
6.3%
1 4221
 
3.9%
, 3719
 
3.5%
3680
 
3.4%
3622
 
3.4%
3253
 
3.0%
( 3174
 
3.0%
) 3174
 
3.0%
3136
 
2.9%
Other values (292) 55566
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65761
61.3%
Space Separator 16997
 
15.8%
Decimal Number 13632
 
12.7%
Other Punctuation 3721
 
3.5%
Open Punctuation 3334
 
3.1%
Close Punctuation 3334
 
3.1%
Dash Punctuation 347
 
0.3%
Uppercase Letter 196
 
0.2%
Lowercase Letter 6
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6789
 
10.3%
3680
 
5.6%
3622
 
5.5%
3253
 
4.9%
3136
 
4.8%
3117
 
4.7%
3097
 
4.7%
2988
 
4.5%
2986
 
4.5%
2984
 
4.5%
Other values (250) 30109
45.8%
Uppercase Letter
ValueCountFrequency (%)
S 68
34.7%
K 64
32.7%
B 17
 
8.7%
A 14
 
7.1%
M 4
 
2.0%
E 4
 
2.0%
G 4
 
2.0%
F 3
 
1.5%
Y 3
 
1.5%
D 3
 
1.5%
Other values (8) 12
 
6.1%
Decimal Number
ValueCountFrequency (%)
1 4221
31.0%
2 2440
17.9%
4 1873
13.7%
3 1710
12.5%
6 708
 
5.2%
0 665
 
4.9%
5 574
 
4.2%
8 509
 
3.7%
9 480
 
3.5%
7 452
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
s 2
33.3%
k 2
33.3%
b 1
16.7%
e 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 3719
99.9%
@ 1
 
< 0.1%
/ 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 3174
95.2%
[ 160
 
4.8%
Close Punctuation
ValueCountFrequency (%)
) 3174
95.2%
] 160
 
4.8%
Space Separator
ValueCountFrequency (%)
16997
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 347
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65761
61.3%
Common 41368
38.5%
Latin 202
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6789
 
10.3%
3680
 
5.6%
3622
 
5.5%
3253
 
4.9%
3136
 
4.8%
3117
 
4.7%
3097
 
4.7%
2988
 
4.5%
2986
 
4.5%
2984
 
4.5%
Other values (250) 30109
45.8%
Latin
ValueCountFrequency (%)
S 68
33.7%
K 64
31.7%
B 17
 
8.4%
A 14
 
6.9%
M 4
 
2.0%
E 4
 
2.0%
G 4
 
2.0%
F 3
 
1.5%
Y 3
 
1.5%
D 3
 
1.5%
Other values (12) 18
 
8.9%
Common
ValueCountFrequency (%)
16997
41.1%
1 4221
 
10.2%
, 3719
 
9.0%
( 3174
 
7.7%
) 3174
 
7.7%
2 2440
 
5.9%
4 1873
 
4.5%
3 1710
 
4.1%
6 708
 
1.7%
0 665
 
1.6%
Other values (10) 2687
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65761
61.3%
ASCII 41570
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16997
40.9%
1 4221
 
10.2%
, 3719
 
8.9%
( 3174
 
7.6%
) 3174
 
7.6%
2 2440
 
5.9%
4 1873
 
4.5%
3 1710
 
4.1%
6 708
 
1.7%
0 665
 
1.6%
Other values (32) 2889
 
6.9%
Hangul
ValueCountFrequency (%)
6789
 
10.3%
3680
 
5.6%
3622
 
5.5%
3253
 
4.9%
3136
 
4.8%
3117
 
4.7%
3097
 
4.7%
2988
 
4.5%
2986
 
4.5%
2984
 
4.5%
Other values (250) 30109
45.8%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct202
Distinct (%)6.8%
Missing1674
Missing (%)36.0%
Infinite0
Infinite (%)0.0%
Mean2553.209
Minimum2400
Maximum12039
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size41.0 KiB
2024-05-11T15:21:47.227538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2400
5-th percentile2428
Q12534
median2555
Q32570
95-th percentile2626
Maximum12039
Range9639
Interquartile range (IQR)36

Descriptive statistics

Standard deviation231.02101
Coefficient of variation (CV)0.090482606
Kurtosis1397.2926
Mean2553.209
Median Absolute Deviation (MAD)16
Skewness36.341813
Sum7585584
Variance53370.705
MonotonicityNot monotonic
2024-05-11T15:21:47.492813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2555 736
15.8%
2565 275
 
5.9%
2571 204
 
4.4%
2570 138
 
3.0%
2569 106
 
2.3%
2604 84
 
1.8%
2532 81
 
1.7%
2418 79
 
1.7%
2534 71
 
1.5%
2516 68
 
1.5%
Other values (192) 1129
24.3%
(Missing) 1674
36.0%
ValueCountFrequency (%)
2400 1
 
< 0.1%
2401 1
 
< 0.1%
2402 1
 
< 0.1%
2403 2
 
< 0.1%
2405 1
 
< 0.1%
2406 14
0.3%
2407 1
 
< 0.1%
2409 8
0.2%
2410 1
 
< 0.1%
2411 1
 
< 0.1%
ValueCountFrequency (%)
12039 1
 
< 0.1%
10366 1
 
< 0.1%
2646 1
 
< 0.1%
2645 1
 
< 0.1%
2644 11
0.2%
2643 6
0.1%
2642 4
 
0.1%
2641 1
 
< 0.1%
2640 3
 
0.1%
2639 10
0.2%
Distinct3030
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
2024-05-11T15:21:47.917073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length6.1916039
Min length1

Characters and Unicode

Total characters28760
Distinct characters737
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2572 ?
Unique (%)55.4%

Sample

1st row서울상회
2nd row만나상회
3rd row서울방앗간
4th row송원방앗간
5th row신진기름집
ValueCountFrequency (%)
주식회사 142
 
2.8%
주)케이프라이드 55
 
1.1%
주)동명에스티유 52
 
1.0%
명류당티에프 50
 
1.0%
선우어묵 45
 
0.9%
주)아일랜드수산 40
 
0.8%
더원씨푸드 39
 
0.8%
주)푸드뱅크코리아 27
 
0.5%
주)행복생활건강 26
 
0.5%
월드푸드 25
 
0.5%
Other values (3199) 4622
90.2%
2024-05-11T15:21:48.597884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1134
 
3.9%
) 995
 
3.5%
( 993
 
3.5%
594
 
2.1%
550
 
1.9%
505
 
1.8%
478
 
1.7%
454
 
1.6%
443
 
1.5%
406
 
1.4%
Other values (727) 22208
77.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25563
88.9%
Close Punctuation 995
 
3.5%
Open Punctuation 993
 
3.5%
Space Separator 478
 
1.7%
Lowercase Letter 303
 
1.1%
Uppercase Letter 249
 
0.9%
Other Punctuation 89
 
0.3%
Decimal Number 81
 
0.3%
Dash Punctuation 6
 
< 0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1134
 
4.4%
594
 
2.3%
550
 
2.2%
505
 
2.0%
454
 
1.8%
443
 
1.7%
406
 
1.6%
390
 
1.5%
369
 
1.4%
344
 
1.3%
Other values (659) 20374
79.7%
Lowercase Letter
ValueCountFrequency (%)
e 46
15.2%
o 32
10.6%
a 24
 
7.9%
s 20
 
6.6%
r 20
 
6.6%
t 19
 
6.3%
m 18
 
5.9%
h 18
 
5.9%
n 14
 
4.6%
i 13
 
4.3%
Other values (14) 79
26.1%
Uppercase Letter
ValueCountFrequency (%)
B 20
 
8.0%
C 19
 
7.6%
I 18
 
7.2%
E 17
 
6.8%
M 17
 
6.8%
S 17
 
6.8%
N 16
 
6.4%
O 15
 
6.0%
H 14
 
5.6%
A 13
 
5.2%
Other values (14) 83
33.3%
Decimal Number
ValueCountFrequency (%)
2 18
22.2%
1 16
19.8%
3 13
16.0%
5 8
9.9%
0 8
9.9%
6 7
 
8.6%
4 5
 
6.2%
8 2
 
2.5%
7 2
 
2.5%
9 2
 
2.5%
Other Punctuation
ValueCountFrequency (%)
& 37
41.6%
, 32
36.0%
. 19
21.3%
' 1
 
1.1%
Close Punctuation
ValueCountFrequency (%)
) 995
100.0%
Open Punctuation
ValueCountFrequency (%)
( 993
100.0%
Space Separator
ValueCountFrequency (%)
478
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25549
88.8%
Common 2645
 
9.2%
Latin 552
 
1.9%
Han 14
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1134
 
4.4%
594
 
2.3%
550
 
2.2%
505
 
2.0%
454
 
1.8%
443
 
1.7%
406
 
1.6%
390
 
1.5%
369
 
1.4%
344
 
1.3%
Other values (649) 20360
79.7%
Latin
ValueCountFrequency (%)
e 46
 
8.3%
o 32
 
5.8%
a 24
 
4.3%
s 20
 
3.6%
r 20
 
3.6%
B 20
 
3.6%
C 19
 
3.4%
t 19
 
3.4%
m 18
 
3.3%
h 18
 
3.3%
Other values (38) 316
57.2%
Common
ValueCountFrequency (%)
) 995
37.6%
( 993
37.5%
478
18.1%
& 37
 
1.4%
, 32
 
1.2%
. 19
 
0.7%
2 18
 
0.7%
1 16
 
0.6%
3 13
 
0.5%
5 8
 
0.3%
Other values (10) 36
 
1.4%
Han
ValueCountFrequency (%)
3
21.4%
2
14.3%
2
14.3%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25549
88.8%
ASCII 3196
 
11.1%
CJK 14
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1134
 
4.4%
594
 
2.3%
550
 
2.2%
505
 
2.0%
454
 
1.8%
443
 
1.7%
406
 
1.6%
390
 
1.5%
369
 
1.4%
344
 
1.3%
Other values (649) 20360
79.7%
ASCII
ValueCountFrequency (%)
) 995
31.1%
( 993
31.1%
478
15.0%
e 46
 
1.4%
& 37
 
1.2%
o 32
 
1.0%
, 32
 
1.0%
a 24
 
0.8%
s 20
 
0.6%
r 20
 
0.6%
Other values (57) 519
16.2%
CJK
ValueCountFrequency (%)
3
21.4%
2
14.3%
2
14.3%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Punctuation
ValueCountFrequency (%)
1
100.0%
Distinct3833
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
Minimum1999-02-13 00:00:00
Maximum2024-05-08 04:15:08
2024-05-11T15:21:48.863192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:21:49.178029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
I
3121 
U
1524 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowI
3rd rowI
4th rowI
5th rowI

Common Values

ValueCountFrequency (%)
I 3121
67.2%
U 1524
32.8%

Length

2024-05-11T15:21:49.434810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:49.601238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3121
67.2%
u 1524
32.8%
Distinct1091
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:21:49.768929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:21:50.343090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
즉석판매제조가공업
4645 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row즉석판매제조가공업
2nd row즉석판매제조가공업
3rd row즉석판매제조가공업
4th row즉석판매제조가공업
5th row즉석판매제조가공업

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 4645
100.0%

Length

2024-05-11T15:21:50.601500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:50.742445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 4645
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1461
Distinct (%)32.2%
Missing109
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean204376.96
Minimum179454.83
Maximum218739.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size41.0 KiB
2024-05-11T15:21:50.936846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum179454.83
5-th percentile203151.45
Q1203357.89
median204081.28
Q3205271.7
95-th percentile206176.18
Maximum218739.38
Range39284.54
Interquartile range (IQR)1913.8118

Descriptive statistics

Standard deviation1131.0668
Coefficient of variation (CV)0.0055342187
Kurtosis56.629737
Mean204376.96
Median Absolute Deviation (MAD)726.69495
Skewness-1.5005256
Sum9.2705388 × 108
Variance1279312.1
MonotonicityNot monotonic
2024-05-11T15:21:51.236203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
204081.282117393 692
 
14.9%
203356.957362754 422
 
9.1%
203996.013917877 242
 
5.2%
205271.704936121 182
 
3.9%
206176.178625746 138
 
3.0%
205396.363734301 98
 
2.1%
204638.486386691 88
 
1.9%
204238.668571436 82
 
1.8%
203347.517232661 66
 
1.4%
205921.350835159 64
 
1.4%
Other values (1451) 2462
53.0%
(Missing) 109
 
2.3%
ValueCountFrequency (%)
179454.835 1
< 0.1%
201997.95066552 1
< 0.1%
201998.969766069 1
< 0.1%
202034.733564967 1
< 0.1%
202036.453390905 1
< 0.1%
202053.32407979 1
< 0.1%
202062.761298766 1
< 0.1%
202096.000930557 1
< 0.1%
202106.009984293 1
< 0.1%
202137.437125277 1
< 0.1%
ValueCountFrequency (%)
218739.375278912 1
 
< 0.1%
211623.404623616 1
 
< 0.1%
206607.014952243 2
 
< 0.1%
206603.229942876 1
 
< 0.1%
206592.423303981 1
 
< 0.1%
206590.046202018 7
0.2%
206586.572428103 4
0.1%
206562.649224959 2
 
< 0.1%
206560.736934242 1
 
< 0.1%
206543.156690365 2
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1461
Distinct (%)32.2%
Missing109
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean453043.67
Minimum450998.64
Maximum464260.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size41.0 KiB
2024-05-11T15:21:51.530244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450998.64
5-th percentile451722.41
Q1452510.85
median453058.67
Q3453187.4
95-th percentile454760.96
Maximum464260.27
Range13261.627
Interquartile range (IQR)676.54586

Descriptive statistics

Standard deviation820.46726
Coefficient of variation (CV)0.0018110114
Kurtosis12.948697
Mean453043.67
Median Absolute Deviation (MAD)265.88659
Skewness1.7198918
Sum2.0550061 × 109
Variance673166.53
MonotonicityNot monotonic
2024-05-11T15:21:51.796373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
453187.395154017 692
 
14.9%
452469.300221465 422
 
9.1%
453058.665828669 242
 
5.2%
452706.897879436 182
 
3.9%
453248.09724644 138
 
3.0%
455131.683241064 98
 
2.1%
451699.765836365 88
 
1.9%
452987.485158497 82
 
1.8%
453035.676205184 66
 
1.4%
452880.100758472 64
 
1.4%
Other values (1451) 2462
53.0%
(Missing) 109
 
2.3%
ValueCountFrequency (%)
450998.638678935 1
 
< 0.1%
451089.9361667 1
 
< 0.1%
451110.245309908 5
0.1%
451122.88876405 1
 
< 0.1%
451129.464809607 1
 
< 0.1%
451134.504571525 1
 
< 0.1%
451139.907793512 1
 
< 0.1%
451153.744333244 1
 
< 0.1%
451164.874072088 1
 
< 0.1%
451168.957999751 1
 
< 0.1%
ValueCountFrequency (%)
464260.265332288 1
 
< 0.1%
462535.865 1
 
< 0.1%
456231.752289367 1
 
< 0.1%
455899.982370316 1
 
< 0.1%
455848.35475815 1
 
< 0.1%
455833.63750058 3
 
0.1%
455813.713540339 1
 
< 0.1%
455808.419175247 1
 
< 0.1%
455803.028832488 1
 
< 0.1%
455790.631069022 17
0.4%

위생업태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
즉석판매제조가공업
3920 
<NA>
725 

Length

Max length9
Median length9
Mean length8.219591
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row즉석판매제조가공업
2nd row즉석판매제조가공업
3rd row즉석판매제조가공업
4th row즉석판매제조가공업
5th row즉석판매제조가공업

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 3920
84.4%
<NA> 725
 
15.6%

Length

2024-05-11T15:21:52.019362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:52.186438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 3920
84.4%
na 725
 
15.6%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
<NA>
4116 
0
 
389
1
 
135
2
 
5

Length

Max length4
Median length4
Mean length3.6583423
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 4116
88.6%
0 389
 
8.4%
1 135
 
2.9%
2 5
 
0.1%

Length

2024-05-11T15:21:52.376772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:52.564307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4116
88.6%
0 389
 
8.4%
1 135
 
2.9%
2 5
 
0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
<NA>
4135 
0
 
403
1
 
107

Length

Max length4
Median length4
Mean length3.6706136
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 4135
89.0%
0 403
 
8.7%
1 107
 
2.3%

Length

2024-05-11T15:21:52.791163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:53.008143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4135
89.0%
0 403
 
8.7%
1 107
 
2.3%

영업장주변구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
<NA>
4070 
기타
 
366
주택가주변
 
184
아파트지역
 
19
유흥업소밀집지역
 
3
Other values (2)
 
3

Length

Max length8
Median length4
Mean length3.8912809
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row기타
2nd row기타
3rd row주택가주변
4th row기타
5th row기타

Common Values

ValueCountFrequency (%)
<NA> 4070
87.6%
기타 366
 
7.9%
주택가주변 184
 
4.0%
아파트지역 19
 
0.4%
유흥업소밀집지역 3
 
0.1%
학교정화(상대) 2
 
< 0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-05-11T15:21:53.203486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:53.427547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4070
87.6%
기타 366
 
7.9%
주택가주변 184
 
4.0%
아파트지역 19
 
0.4%
유흥업소밀집지역 3
 
0.1%
학교정화(상대 2
 
< 0.1%
학교정화(절대 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
<NA>
4070 
기타
447 
관리
 
74
자율
 
42
 
10

Length

Max length4
Median length4
Mean length3.7502691
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자율
2nd row자율
3rd row기타
4th row자율
5th row자율

Common Values

ValueCountFrequency (%)
<NA> 4070
87.6%
기타 447
 
9.6%
관리 74
 
1.6%
자율 42
 
0.9%
10
 
0.2%
우수 2
 
< 0.1%

Length

2024-05-11T15:21:53.683195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:53.900236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4070
87.6%
기타 447
 
9.6%
관리 74
 
1.6%
자율 42
 
0.9%
10
 
0.2%
우수 2
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
<NA>
3471 
상수도전용
1174 

Length

Max length5
Median length4
Mean length4.2527449
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상수도전용
2nd row상수도전용
3rd row상수도전용
4th row상수도전용
5th row상수도전용

Common Values

ValueCountFrequency (%)
<NA> 3471
74.7%
상수도전용 1174
 
25.3%

Length

2024-05-11T15:21:54.107698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:54.259841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3471
74.7%
상수도전용 1174
 
25.3%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
<NA>
4440 
0
 
205

Length

Max length4
Median length4
Mean length3.8675996
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4440
95.6%
0 205
 
4.4%

Length

2024-05-11T15:21:54.429439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:54.607395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4440
95.6%
0 205
 
4.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
<NA>
3101 
0
1544 

Length

Max length4
Median length4
Mean length3.0027987
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 3101
66.8%
0 1544
33.2%

Length

2024-05-11T15:21:54.794810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:55.006387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3101
66.8%
0 1544
33.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
<NA>
3101 
0
1544 

Length

Max length4
Median length4
Mean length3.0027987
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 3101
66.8%
0 1544
33.2%

Length

2024-05-11T15:21:55.293763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:55.542190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3101
66.8%
0 1544
33.2%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
<NA>
3096 
0
1540 
1
 
7
2
 
2

Length

Max length4
Median length4
Mean length2.9995694
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 3096
66.7%
0 1540
33.2%
1 7
 
0.2%
2 2
 
< 0.1%

Length

2024-05-11T15:21:55.756554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:56.058105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3096
66.7%
0 1540
33.2%
1 7
 
0.2%
2 2
 
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
<NA>
3095 
0
1541 
1
 
9

Length

Max length4
Median length4
Mean length2.9989236
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 3095
66.6%
0 1541
33.2%
1 9
 
0.2%

Length

2024-05-11T15:21:56.342679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:56.572999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3095
66.6%
0 1541
33.2%
1 9
 
0.2%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
<NA>
2449 
자가
1346 
임대
850 

Length

Max length4
Median length4
Mean length3.0544672
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2449
52.7%
자가 1346
29.0%
임대 850
 
18.3%

Length

2024-05-11T15:21:56.844768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:57.059595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2449
52.7%
자가 1346
29.0%
임대 850
 
18.3%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
<NA>
4167 
0
476 
10000000
 
2

Length

Max length8
Median length4
Mean length3.6942949
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4167
89.7%
0 476
 
10.2%
10000000 2
 
< 0.1%

Length

2024-05-11T15:21:57.283359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:57.487348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4167
89.7%
0 476
 
10.2%
10000000 2
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.4 KiB
<NA>
4168 
0
476 
950000
 
1

Length

Max length6
Median length4
Mean length3.6930032
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4168
89.7%
0 476
 
10.2%
950000 1
 
< 0.1%

Length

2024-05-11T15:21:57.690022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:21:57.906876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4168
89.7%
0 476
 
10.2%
950000 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing725
Missing (%)15.6%
Memory size9.2 KiB
False
3920 
(Missing)
725 
ValueCountFrequency (%)
False 3920
84.4%
(Missing) 725
 
15.6%
2024-05-11T15:21:58.058007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct309
Distinct (%)7.9%
Missing725
Missing (%)15.6%
Infinite0
Infinite (%)0.0%
Mean5.2935
Minimum0
Maximum239.15
Zeros3042
Zeros (%)65.5%
Negative0
Negative (%)0.0%
Memory size41.0 KiB
2024-05-11T15:21:58.275846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile33
Maximum239.15
Range239.15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation15.308214
Coefficient of variation (CV)2.8918889
Kurtosis44.432726
Mean5.2935
Median Absolute Deviation (MAD)0
Skewness5.3233902
Sum20750.52
Variance234.34142
MonotonicityNot monotonic
2024-05-11T15:21:58.621742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3042
65.5%
3.3 127
 
2.7%
33.0 43
 
0.9%
10.0 39
 
0.8%
6.6 37
 
0.8%
9.9 22
 
0.5%
20.0 19
 
0.4%
16.5 19
 
0.4%
13.2 18
 
0.4%
30.0 17
 
0.4%
Other values (299) 537
 
11.6%
(Missing) 725
 
15.6%
ValueCountFrequency (%)
0.0 3042
65.5%
1.0 1
 
< 0.1%
1.2 1
 
< 0.1%
1.71 1
 
< 0.1%
2.0 16
 
0.3%
3.0 8
 
0.2%
3.2 1
 
< 0.1%
3.3 127
 
2.7%
3.38 1
 
< 0.1%
3.4 1
 
< 0.1%
ValueCountFrequency (%)
239.15 1
< 0.1%
220.29 1
< 0.1%
181.7 1
< 0.1%
153.34 1
< 0.1%
132.0 2
< 0.1%
128.75 1
< 0.1%
119.0 1
< 0.1%
116.69 1
< 0.1%
116.0 1
< 0.1%
115.69 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4645
Missing (%)100.0%
Memory size41.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4645
Missing (%)100.0%
Memory size41.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4645
Missing (%)100.0%
Memory size41.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030500003050000-107-1972-0008019720418<NA>1영업/정상1영업<NA><NA><NA><NA>022213500712.40130854서울특별시 동대문구 전농동 295-52 북동16호,남동특1호 (전농로147)<NA><NA>서울상회2018-07-24 14:23:40I2018-08-31 23:59:59.0즉석판매제조가공업204970.901636452852.821037즉석판매제조가공업11기타자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
130500003050000-107-1972-0008119720427<NA>1영업/정상1영업<NA><NA><NA><NA>02 962483021.94130862서울특별시 동대문구 제기동 630 [왕산로35길27]서울특별시 동대문구 왕산로35길 27 (제기동,[왕산로35길27])2572만나상회2010-11-30 11:18:22I2018-08-31 23:59:59.0즉석판매제조가공업203715.400333453179.944667즉석판매제조가공업<NA><NA>기타자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
230500003050000-107-1972-0069819721109<NA>1영업/정상1영업<NA><NA><NA><NA>02 962087225.50130867서울특별시 동대문구 청량리동 61-320 (청소년3길14)서울특별시 동대문구 제기로33길 5 (청량리동,(청소년3길14))2462서울방앗간2007-05-09 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업204246.02541453814.181725즉석판매제조가공업<NA><NA>주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
330500003050000-107-1972-0071019720330<NA>1영업/정상1영업<NA><NA><NA><NA>022249120512.00130854서울특별시 동대문구 전농동 295-52 시장북동34호 (전농로147)<NA><NA>송원방앗간2012-07-19 15:37:32I2018-08-31 23:59:59.0즉석판매제조가공업204970.901636452852.821037즉석판매제조가공업11기타자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
430500003050000-107-1972-0071119720330<NA>1영업/정상1영업<NA><NA><NA><NA>022212402113.50130854서울특별시 동대문구 전농동 295-431 1층서울특별시 동대문구 전농로15길 21, 1층 (전농동, 제2서-2)2547신진기름집2013-01-28 14:34:06I2018-08-31 23:59:59.0즉석판매제조가공업204915.75106452833.413459즉석판매제조가공업11기타자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
530500003050000-107-1972-0071219720330<NA>3폐업2폐업20051115<NA><NA><NA>022212225112.00130854서울특별시 동대문구 전농동 295-52 시장남동51호<NA><NA>삼흥기름집1999-04-09 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업204970.901636452852.821037즉석판매제조가공업11기타자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
630500003050000-107-1972-0071319720404<NA>3폐업2폐업20020822<NA><NA><NA>02 923891320.24130823서울특별시 동대문구 용두동 231-5<NA><NA>대동기름집2000-03-10 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업202538.011841452901.185284즉석판매제조가공업11주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
730500003050000-107-1972-0071419720425<NA>1영업/정상1영업<NA><NA><NA><NA>02 928048312.35130823서울특별시 동대문구 용두동 232-1 (2호) [한빛로58-2]서울특별시 동대문구 한빛로 58-2 (용두동,(2호) [한빛로58-2])2579경북기름집2011-07-01 16:39:04I2018-08-31 23:59:59.0즉석판매제조가공업202505.816545452931.438064즉석판매제조가공업<NA><NA>기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
830500003050000-107-1972-0071619720501<NA>3폐업2폐업20031125<NA><NA><NA>02 923415212.78130823서울특별시 동대문구 용두동 209-4<NA><NA>진미기름집1999-04-12 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업202482.040682452934.654942즉석판매제조가공업<NA><NA>기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
930500003050000-107-1972-0071719720512<NA>3폐업2폐업20001130<NA><NA><NA>02 962180215.00130826서울특별시 동대문구 이문동 292-87<NA><NA>삼양기름집2000-12-02 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
463530500003050000-107-2024-000852024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30130-851서울특별시 동대문구 전농동 591-53 청량리역,롯데백화점서울특별시 동대문구 왕산로 214, 롯데백화점 지하2층 (전농동)2555이스터에그2024-04-26 09:47:11I2023-12-03 22:08:00.0즉석판매제조가공업204081.282117453187.395154<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
463630500003050000-107-2024-000862024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA>070430095893.30130-851서울특별시 동대문구 전농동 591-53 청량리역,롯데백화점서울특별시 동대문구 왕산로 214, 청량리역,롯데마트 4층 (전농동)2555명류당티에프2024-04-29 13:07:12I2023-12-05 00:01:00.0즉석판매제조가공업204081.282117453187.395154<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
463730500003050000-107-2024-000872024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA>031 76792243.30130-835서울특별시 동대문구 장안동 94-27 장안동 마루하우스서울특별시 동대문구 한천로46길 42, 장안동 마루하우스 1층 (장안동)2516(주)메르시푸드2024-04-29 15:14:23I2023-12-05 00:01:00.0즉석판매제조가공업206176.178626453248.097246<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
463830500003050000-107-2024-000882024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30130-851서울특별시 동대문구 전농동 591-53 청량리역,롯데백화점서울특별시 동대문구 왕산로 214, 청량리역사 3층 (전농동)2555미르2024-04-30 10:44:40I2023-12-05 00:02:00.0즉석판매제조가공업204081.282117453187.395154<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
463930500003050000-107-2024-000892024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>116.10130-817서울특별시 동대문구 용두동 39-61서울특별시 동대문구 천호대로35길 65, 1층 (용두동)2562동경제면2024-04-30 16:09:13I2023-12-05 00:02:00.0즉석판매제조가공업203660.009372452656.852465<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
464030500003050000-107-2024-000902024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.66130-080서울특별시 동대문구 이문동 431 이문 월드메르디앙 힐트리움 더 테라스서울특별시 동대문구 이문로9길 105-13, 근린생활시설동 T05호 (이문동, 이문 월드메르디앙 힐트리움 더 테라스)2451용토끼2024-05-02 14:23:27U2023-12-05 00:04:00.0즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
464130500003050000-107-2024-000912024-05-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30130-826서울특별시 동대문구 이문동 292-10 이문동 웰츠타워서울특별시 동대문구 이문로 136, 지하1층 (이문동, 이문동 웰츠타워)2418(주)케이프라이드2024-05-01 13:06:17I2023-12-05 00:03:00.0즉석판매제조가공업205396.363734455131.683241<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
464230500003050000-107-2024-000922024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30130-848서울특별시 동대문구 전농동 10 전농 SK아파트서울특별시 동대문구 사가정로 148, 1층 (전농동, 전농 SK아파트)2532철이푸드2024-05-07 14:26:47I2023-12-05 00:09:00.0즉석판매제조가공업205271.704936452706.897879<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
464330500003050000-107-2024-000932024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA>02228163403.30130-851서울특별시 동대문구 전농동 591-53 청량리역,롯데백화점서울특별시 동대문구 왕산로 214, 청량리역 3층 (전농동)2555주식회사 지오에프앤씨2024-05-07 14:34:12I2023-12-05 00:09:00.0즉석판매제조가공업204081.282117453187.395154<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
464430500003050000-107-2024-000942024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30130-817서울특별시 동대문구 용두동 33-1 홈플러스 동대문점서울특별시 동대문구 천호대로 133, 홈플러스 동대문점 지하2층 (용두동)2565(주)케이프라이드2024-05-07 15:06:52I2023-12-05 00:09:00.0즉석판매제조가공업203356.957363452469.300221<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>